SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching P06786 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MSTEPVSASDKYQKISQLEHILKRPDTYIGSVETQEQLQWIYDEETDCMI    50
  51  EKNVTIVPGLFKIFDEILVNAADNKVRDPSMKRIDVNIHAEEHTIEVKND   100
 101  GKGIPIEIHNKENIYIPEMIFGHLLTSSNYDDDEKKVTGGRNGYGAKLCN   150
 151  IFSTEFILETADLNVGQKYVQKWENNMSICHPPKITSYKKGPSYTKVTFK   200
 201  PDLTRFGMKELDNDILGVMRRRVYDINGSVRDINVYLNGKSLKIRNFKNY   250
 251  VELYLKSLEKKRQLDNGEDGAAKSDIPTILYERINNRWEVAFAVSDISFQ   300
 301  QISFVNSIATTMGGTHVNYITDQIVKKISEILKKKKKKSVKSFQIKNNMF   350
 351  IFINCLIENPAFTSQTKEQLTTRVKDFGSRCEIPLEYINKIMKTDLATRM   400
 401  FEIADANEENALKKSDGTRKSRITNYPKLEDANKAGTKEGYKCTLVLTEG   450
 451  DSALSLAVAGLAVVGRDYYGCYPLRGKMLNVREASADQILKNAEIQAIKK   500
 501  IMGLQHRKKYEDTKSLRYGHLMIMTDQDHDGSHIKGLIINFLESSFPGLL   550
 551  DIQGFLLEFITPIIKVSITKPTKNTIAFYNMPDYEKWREEESHKFTWKQK   600
 601  YYKGLGTSLAQEVREYFSNLDRHLKIFHSLQGNDKDYIDLAFSKKKADDR   650
 651  KEWLRQYEPGTVLDPTLKEIPISDFINKELILFSLADNIRSIPNVLDGFK   700
 701  PGQRKVLYGCFKKNLKSELKVAQLAPYVSECTAYHHGEQSLAQTIIGLAQ   750
 751  NFVGSNNIYLLLPNGAFGTRATGGKDAAAARYIYTELNKLTRKIFHPADD   800
 801  PLYKYIQEDEKTVEPEWYLPILPMILVNGAEGIGTGWSTYIPPFNPLEII   850
 851  KNIRHLMNDEELEQMHPWFRGWTGTIEEIEPLRYRMYGRIEQIGDNVLEI   900
 901  TELPARTWTSTIKEYLLLGLSGNDKIKPWIKDMEEQHDDNIKFIITLSPE   950
 951  EMAKTRKIGFYERFKLISPISLMNMVAFDPHGKIKKYNSVNEILSEFYYV  1000
1001  RLEYYQKRKDHMSERLQWEVEKYSFQVKFIKMIIEKELTVTNKPRNAIIQ  1050
1051  ELENLGFPRFNKEGKPYYGSPNDEIAEQINDVKGATSDEEDEESSHEDTE  1100
1101  NVINGPEELYGTYEYLLGMRIWSLTKERYQKLLKQKQEKETELENLLKLS  1150
1151  AKDIWNTDLKAFEVGYQEFLQRDAEARGGNVPNKGSKTKGKGKRKLVDDE  1200
1201  DYDPSKKNKKSTARKGKKIKLEDKNFERILLEQKLVTKSKAPTKIKKEKT  1250
1251  PSVSETKTEEEENAPSSTSSSSIFDIKKEDKDEGELSKISNKFKKISTIF  1300
1301  DKMGSTSATSKENTPEQDDVATKKNQTTAKKTAVKPKLAKKPVRKQQKVV  1350
1351  ELSGESDLEILDSYTDREDSNKDEDDAIPQRSRRQRSSRAASVPKKSYVE  1400
1401  TLELSDDSFIEDDEEENQGSDVSFNEED                        1428

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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